Market Making with Traders
A new method using natural language processing (NLP) has been suggested for classifying AI stocks, providing a cost-effective alternative that outperforms existing AI-themed ETFs.
20 shares17 citations todaySource ↗
Quant LetterNo. 81
189 items across 10 sections, as sent to readers on 8 January 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
21 items
A new method using natural language processing (NLP) has been suggested for classifying AI stocks, providing a cost-effective alternative that outperforms existing AI-themed ETFs.
20 shares17 citations todaySource ↗
A study introduces a new way to classify AI stocks using NLP, offering a more transparent and competitive approach to AI investment that matches or exceeds current AI-themed ETFs.
20 shares17 citations todaySource ↗
A study explores solutions to an optimal liquidity provision problem in a market with different types of traders, aiming to extract market trend information from anonymous orders.
7 shares6 citations todaySource ↗
The paper highlights the shortcomings of generative models in finance, suggesting a method for generating multivariate returns that meets standard evaluations and aligns with observed asset returns.
6 shares10 citations todaySource ↗
The article explores the shortcomings of generative models in finance, specifically in portfolio and risk management, and suggests a method for generating multivariate returns that aligns with standard evaluations.
6 shares10 citations todaySource ↗
The paper introduces a framework for portfolio allocation that uses multiple hypotheses prediction through structured ensemble models, allowing for control of portfolio diversification before decision-making.
6 shares2 citations todaySource ↗
The research examines the relationships between different maturity stock index futures contracts in China's financial futures market, uncovering a regular pattern of price discovery and a profitable trading strategy based on this pattern.
5 shares1 citation todaySource ↗
The study shows that in a simple, arbitrage-free market, a unique prediction of random risk aversion exists that ensures consistency of optimal strategies over any time period for a certain type of state-dependent exponential utilities.
5 shares1 citation todaySource ↗
A Chinese study suggests that technology advancements and random resource allocation can reduce income inequality, based on data from vehicle license plates.
8 sharesSource ↗
A study on economics PhD programs found that active research advisors help students publish more, but don't necessarily increase their success, and female productivity peaks earlier than male.
8 shares5 citations todaySource ↗
Research across 56 countries shows that a slight increase in capital share significantly raises the income share of the top 5%, contributing to half of the rise in income inequality.
8 shares1 citation todaySource ↗
The same research reiterated that a minor increase in capital share significantly boosts the income share of the top 5%, accounting for half of the increase in income inequality.
8 shares1 citation todaySource ↗
The research finds that income is often underreported in surveys due to non-random consent to data linkage, based on an analysis of German social security and survey data.
7 sharesSource ↗
The study concludes that stock prices on the Warsaw Stock Exchange do not follow Benford's law due to their non-random distribution and market inefficiency.
7 sharesSource ↗
The paper reveals that the EU27 automotive sector is increasingly dependent on non-EU suppliers, especially China, and competitiveness is shifting towards Eastern European countries.
6 shares2 citations todaySource ↗
The study highlights the need for strategic investments and government interventions to manage transition risks in sectors affected by the shift to a low-carbon economy.
6 shares2 citations todaySource ↗
The article discusses a method to validate the assumptions of a Lévy-Driven Ornstein-Uhlenbeck process using real data. It includes steps to estimate model parameters and approximate the driving process, with the effectiveness of the method shown through simulation.
5 sharesSource ↗
Research shows that a karma-based credit system has significant benefits, especially in high-urgency situations, offering insights for future practical applications.
25 shares4 citations todaySource ↗
A study finds that Large Language Models (LLMs) can address US personal finance issues with 70% accuracy, but struggle with complex financial queries.
15 shares17 citations todaySource ↗
A new stock trading framework, TradingAgents, uses LLM-powered agents to potentially enhance trading performance by mimicking real-world trading firm dynamics.
13 shares220 citations todaySource ↗
Research on Japan's labor market shows a decreasing trend in job matching efficiency for both full and part-time positions, with occupational mismatches being more prevalent than geographical ones.
11 sharesSource ↗
Working papers in finance and economics from SSRN.
54 items
The study finds that trading strategies based on linear predictive models perform poorly due to overfitting when they involve many assets and weak trading signals.
14 sharesSource ↗
The paper discusses the evolution of private equity, its performance during downturns, the role of uninvested capital (dry powder), and the challenges of regulation and transparency.
5 sharesSource ↗
The study reveals that financial literacy, particularly understanding of beta and alpha, leads to better investment choices and improved returns in a robo-advising setup.
3 sharesSource ↗
The article highlights the role of online reviews in customer decision-making, the potential for supplier abuse, and the use of machine learning to identify genuine reviews.
4 shares2 citations todaySource ↗
The study shows that prediction markets can help understand the relationship between financial markets and political candidates, with systematic portfolios outperforming the benchmark during election cycles.
6 sharesSource ↗
The research introduces a multidimensional investment model that adapts to new information and is robust to parameter misspecification, using a continuous-time estimator for drift parameters.
6 sharesSource ↗
The article finds that the Limit Up/Limit Down Amendment has reduced unnecessary trading pauses and improved liquidity for individual stocks, but has also increased short-term volatility.
2 sharesSource ↗
The article suggests a computer vision-based antenna system that enhances the precision and reliability of 5G communication systems by adjusting the base station antenna's radiation pattern and beam direction.
4 sharesSource ↗
The study reveals that monetary tightening worsens financial stress after supply shocks, recommending less aggressive monetary policy tightening when financial fragility is present.
3 sharesSource ↗
The paper presents a method for multimaterial topology optimization that calculates stress individually for each material phase, removing the need for stress limit interpolation.
10 sharesSource ↗
The research explores the link between top management team diversity and firm performance in large non-financial Chinese companies, finding positive effects from cognitive and functional background diversity.
6 sharesSource ↗
The study introduces a machine learning-based predictive framework for forecasting tensile properties of aluminum alloys, providing a cost-effective method to optimize alloy design.
2 sharesSource ↗
The study creates a multitask deep learning approach to predict lane-level pavement performance using historical data, tested with a real case in China.
2 sharesSource ↗
The manuscript discusses the potential of AI and ML in finance and regulatory compliance, but also points out challenges related to data privacy, algorithmic bias, and model explainability.
3 shares5 citations todaySource ↗
The paper suggests a density-adaptive threshold data augmentation algorithm to enhance defect pattern recognition in semiconductor wafer maps, based on a detailed analysis of defect distribution characteristics.
3 sharesSource ↗
The article proves the mathematical similarity between decision trees and artificial neural networks, hinting at combined machine learning methods.
37 sharesSource ↗
The study assesses Machine Learning's role in financial analytics, emphasizing its potential in personal finance and the need to address data privacy and bias.
30 sharesSource ↗
The paper compares Kolmogorov-Arnold Networks and traditional Artificial Neural Networks, showing a balance between theoretical accuracy and practical scalability.
81 sharesSource ↗
Hierarchical Reinforcement Learning for Banks: BANKRL, a new framework for bank management using multiagent reinforcement learning, balances profitability, risk, and regulatory compliance.
41 sharesSource ↗
Historical Perspective 1948-2024: The paper suggests that integrating Agent-Based Models, Reinforcement Learning agents, and Large Language Model agents can solve complex real-world problems.
77 sharesSource ↗
Takeover Rumor Verification: The study uses machine learning to predict the accuracy of corporate takeover rumors, finding TabNet to be the most effective and emphasizing the need to address data imbalance.
8 sharesSource ↗
The study finds that brokers have a strategic advantage over traders in a broker-mediated market due to information leakage in client trading flow.
15 sharesSource ↗
Large Language Models are utilized to study China's industrial policies from 2000-2022, using data from 3 million government documents.
31 shares15 citations todaySource ↗
A model explores the dynamics of Bitcoin's market price, focusing on intrinsic value and speculative behavior, backed by empirical analysis.
15 sharesSource ↗
The ability of mutual fund managers to generate positive alpha around Federal Open Market Committee meetings is tied to monetary policy uncertainty.
6 sharesSource ↗
Hedge fund leverage is positively linked to prime brokers' stock price crash risk, with certain strategies reducing risk metrics.
11 sharesSource ↗
Topic-level sentiment analysis using machine learning can offer valuable insights for data-driven decision-making.
2 sharesSource ↗
The stability of deep neural nets is examined from a weak dependence perspective, suggesting a new loss function for improved stability.
4 sharesSource ↗
A new deep learning method, CLVSA, is proposed for predicting financial market movement in Chinese futures markets.
4 sharesSource ↗
The combination of PySpark and machine learning on the Databricks platform can boost predictive analytics, streamline model training, and enhance prediction accuracy.
2 sharesSource ↗
The article introduces GeomTop, a neural architecture that combines geometric convolutions with persistence-based features for data analysis in molecular dynamics and materials science.
31 sharesSource ↗
The article extends the FeynmanKac formula to nonMarkovian settings, providing a mathematical framework for complex memory effects in stochastic processes and financial derivatives pricing.
24 sharesSource ↗
The article explores the relationship between Q-learning and the HamiltonJacobiBellman equation, discussing the conditions needed for the existence, uniqueness, and stability of viscosity solutions and Q-learning's convergence.
15 sharesSource ↗
The article suggests that annual rebalancing of index funds could improve returns by 40 bps per year, due to adverse selection costs from changes in the stock market composition.
3 sharesSource ↗
A study shows a positive link between bond and equity returns, with less stakeholder conflict leading to more comovement, emphasizing the need for good corporate governance and regulations.
3 sharesSource ↗
The valuation of music royalty assets is based on predicting future revenues and creating a discounted cashflow model, with the asset's value related to the age of its songs.
5 sharesSource ↗
Cryptocurrencies, due to their high volatility and regulatory uncertainty, are not suitable as main treasury reserves, highlighting the importance of traditional instruments like Treasury securities.
2 sharesSource ↗
Liquidity provision strategies can be more profitable than holding assets, as pricing functions can be designed to maximize the expected time a liquidity provider stays in the pool.
2 sharesSource ↗
Web3 technologies could solve issues in the U.S. tech sector, such as data security and Big Tech monopolies, by promoting a decentralized digital ecosystem that prioritizes data ownership and security.
2 sharesSource ↗
Active exchange-traded funds (AETFs) help investors weed out underperforming managers, leading to better sector efficiency and performance than mutual and passive funds.
9 sharesSource ↗
The risk transfer among U.S. investors is minimal, challenging macrofinance models that forecast larger risk transfers due to fluctuating equity premiums.
5 sharesSource ↗
Asset returns are vulnerable to climate risk; adding commodities to a portfolio can enhance diversification during climate stress but may also increase tracking error and lower risk-adjusted performance.
2 sharesSource ↗
A dynamic portfolio optimization framework that includes individual financial health metrics can effectively balance risk and return, customizing asset allocation to individual profiles.
2 sharesSource ↗
Bitcoin's volatility shows significant clustering, especially in shorter time frames, enabling statistically significant predictions of market movements.
2 sharesSource ↗
A general equilibrium model that takes into account investors' actual objectives provides a more realistic perspective of asset pricing, with Brazil's innovative retirement and education bonds serving as examples.
3 sharesSource ↗
Monetary policy affects hedging costs by altering state variables and impacting option market liquidity, with significant changes in hedging costs seen during the peak of the pandemic crisis.
2 sharesSource ↗
AI-powered deepfake technology threatens financial markets by manipulating market sentiment, disrupting trading systems, and exploiting retail investors.
2 sharesSource ↗
BlackRock, State Street Corporation, and Vanguard Group are being sued by eleven US State Attorneys General for allegedly forcing a reduction in coal production.
21 shares1 citation todaySource ↗
Portfolio efficiency can be significantly improved by mixing risky assets with a market fund instead of borrowing more capital.
2 sharesSource ↗
Sustainable finance needs a shift from financial value maximisation to integrated value balancing, incorporating financial, social, and environmental value.
3 sharesSource ↗
A portfolio strategy using Monte Carlo simulations and insider trading transactions consistently outperforms the S&P 500.
3 sharesSource ↗
Personal portfolio choice should align with the investor's risk aversion, and a mismatch between actual and targeted risks can lead to penalties.
2 sharesSource ↗
Understanding volatility connectedness among theme factors and sector indices in the Chinese stock market is key for effective investment strategies and risk management.
3 sharesSource ↗
Stocks with higher rebalancing fund ownership show smaller price reactions to earnings surprises, indicating that asset allocation mandates influence stock price reactions.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
24 items
The article examines the effect of different covariance estimators on portfolio selection, concluding that traditional sample covariance matrix performs best.
21 sharesSource ↗
The paper presents a new insider trading model, showing that increased correlation coefficient leads to more informative prices, less trading, and lower insider profits.
15 sharesSource ↗
The study uses mathematical models to calculate the capital valuation adjustment, utilizing a semi-replication strategy based on market theory.
9 sharesSource ↗
The research proposes a new criterion for determining the number of factors in static approximate factor models, demonstrating its effectiveness through a Monte Carlo study.
6 sharesSource ↗
The article finds that robust Haberman linking performs better than invariance alignment for factor models when item intercepts are used, with varying results for different loss functions.
2 sharesSource ↗
Research shows China, the US, and England are leading in AI education research, with future trends including AI-VR integration, sentiment analysis, and predictive student performance models.
4 sharesSource ↗
A new finance forecasting method, multi-view locally weighted regression (MVLWR), which combines multi-view and ensemble learning, has been found to outperform other methods in predicting loss given default.
1 sharesSource ↗
A study found that XGBoost performs better in predicting inflation during economic crises in Turkey with large datasets, while the ARMA model performs better with smaller datasets.
1 sharesSource ↗
The study introduces a new method to solve single-agent stochastic games using matrix norms, providing a comprehensive approach that considers all stages and actions at once.
1 sharesSource ↗
The research shows that Large Language Models can improve clustering accuracy in marketing research for consumer segmentation and can be used to develop persona chatbots that mimic consumer preferences.
1 sharesSource ↗
The study compares the gender accuracy in English-Arabic machine translation of two large language models, Gemini and ChatGPT, with Gemini performing better in handling gender-related translation issues.
0 sharesSource ↗
The article finds that ChatGPT, a large language model-based chatbot, is more effective than Bing Chat in detecting the truthfulness of political information across various languages and political communication concepts.
0 sharesSource ↗
The first article presents a model to analyze product attributes' significance and their effect on customer satisfaction using online reviews, aiding businesses in strategizing product enhancements.
7 sharesSource ↗
The second article employs social network analysis to comprehend the traits of 'believer' and 'denier' groups in online debates, assisting in predicting information dissemination and controlling disinformation spread.
4 sharesSource ↗
Research shows machine learning credit scoring models may introduce algorithmic bias and lessen human expert involvement by focusing on data trails.
43 sharesSource ↗
A study using machine learning to analyze stock market volatility found the RF-LASSO model to be the most accurate in forecasting.
24 sharesSource ↗
An in-depth study of algorithmic trading strategies in the Shanghai Futures Exchange found none to be successful, indicating the market's volatility.
24 sharesSource ↗
The XGBoost machine learning algorithm was found to be the most effective in predicting crises in the African stock market, with historical prices and exchange rates as key factors.
22 sharesSource ↗
A study found that using deep learning models and sentiment analysis to predict salmon spot prices improved accuracy, with the CNN-LSTM model performing the best.
19 sharesSource ↗
The research finds that combining different methods and wavelet analysis can effectively predict exchange rate volatility using financial and macroeconomic factors.
19 sharesSource ↗
The study reveals a link between the wealth of European countries and their investment in sin stocks, with richer Northern European countries having higher risk-adjusted returns.
16 sharesSource ↗
The paper discovers that imported sovereign risks from developing G20 countries have a more significant impact on China under normal conditions.
15 sharesSource ↗
The thesis demonstrates that an automated Bitcoin trading strategy built using Informer architecture and trained with the GMADL loss function is superior to other strategies.
15 sharesSource ↗
The research expands on methods for nonnegative constraints in portfolio optimization, confirming the presence of both positive and negative elements in optimal solution sets.
15 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
16 items
The MeCo method speeds up language model pre-training by using additional learning cues, allowing the model to work without metadata and enhancing task performance.
114 shares22 citations todaySource ↗
Vision and Speech Interaction: A proposed training methodology enables Large Language Models to comprehend visual and speech data, improving speech-to-speech dialogue capabilities and response speed.
52 shares230 citations todaySource ↗
Video Generation and Camera Pose Estimation: Research into 3D awareness in video generators shows that task-specific supervision greatly improves their accuracy for camera pose estimation.
44 shares7 citations todaySource ↗
Point Tracking: ProTracker, a new video tracking framework, combines optical flow estimations and semantic features, outperforming other unsupervised and self-supervised methods.
36 shares4 citations todaySource ↗
3D Reconstruction from Videos: VideoLifter, a new framework, optimizes 3D representation from video sequences, speeding up the reconstruction process and surpassing other methods in visual fidelity and efficiency.
33 shares10 citations todaySource ↗
The study presents a new visual localization method using a covisibility graph-based global encoding learning and data augmentation strategy, achieving top results on large-scale datasets without needing network ensembles or 3D supervision.
24 shares28 citations todaySource ↗
The research introduces tools for detecting AI-generated content in student work using machine learning and deep learning algorithms, aiming to uphold academic integrity and responsible AI use in education.
14 shares16 citations todaySource ↗
The paper proposes a new model, VA-VAE, that aligns the latent space with pre-trained vision foundation models, enabling faster convergence of Diffusion Transformers in high-dimensional latent spaces and achieving top performance on ImageNet 256x256 generation.
14 shares395 citations todaySource ↗
The article introduces BoostStep, a method that enhances the reasoning quality within each step of large language models solving complex math problems, providing more relevant examples and integrating seamlessly with Monte Carlo Tree Search methods.
13 shares19 citations todaySource ↗
The study presents Nested Attention, a mechanism that injects a rich and expressive image representation into the model's existing cross-attention layers, enabling high identity preservation while adhering to input text prompts in personalizing text-to-image models.
12 shares24 citations todaySource ↗
The article discusses MEDEC, a benchmark for identifying and fixing medical errors in clinical notes, and reveals that while Large Language Models (LLMs) are effective, they are still not as accurate as medical doctors.
560 shares140 citations todaySource ↗
The paper introduces RhoFold+, a deep learning method that accurately predicts 3D structures of single-chain RNAs from sequences, surpassing existing methods and aiding in RNA structure and function research.
86 shares245 citations todaySource ↗
The research introduces a flexible framework for symmetrising neural networks using group homomorphism, showcasing the usefulness of Markov categories in tackling complex machine learning problems.
55 shares7 citations todaySource ↗
Sound Effects Tool: Stable-V2A is a two-stage model that automates repetitive tasks in audio creation for video scenes, aiding sound designers in focusing on creative aspects.
44 shares5 citations todaySource ↗
The study presents a PD-LMC algorithm that samples from a probability distribution while meeting statistical constraints, useful in Bayesian inference and prediction fairness.
35 shares15 citations todaySource ↗
Online RAG: EdgeRAG is a system proposed for deploying Retrieval Augmented Generation on devices with limited resources, reducing latency and memory usage by pruning and generating embeddings as needed.
23 shares27 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
11 items
Language model chatbots and generative search engines excel at answering specific queries but struggle to uncover unknown information.
15,769 shares
LLM Pretraining with PyTorch: Significant accelerations were achieved at various GPU scales by stacking training optimizations, proving the effectiveness of parallelism.
2,920 shares
Interaction with Language Models: Recent Multimodal Large Language Models have mainly focused on integrating visual and text modalities, overlooking the importance of speech in enhancing interaction.
1,452 shares
Diffusion Models for Lip Sync: The experience with SyncNet can be applied to other lip sync and audio-driven portrait animation methods without altering the overall training framework.
201 shares
Parallelizable Implementation: A fully parallelizable memory layer implementation is offered, demonstrating scaling laws with up to 128B memory parameters, pre-trained to 1 trillion tokens.
172 shares
Recent studies show that Large Language Models (LLMs) can efficiently process tasks from various modalities by converting multimodal information into tokens to predict the next one based on context.
164 shares
TangoFlux, a Text-to-Audio generative model with 515M parameters, can produce up to 30 seconds of 44.1kHz audio in just 3.7 seconds using a single A40 GPU.
117 shares
A new benchmark aims to improve the understanding of world knowledge by Large Language Models (LLMs) to prevent both unintentional and malicious data leakage.
112 shares
The first article presents a new technique called Self-supervised Hierarchical Makeup Transfer (SHMT) that improves makeup transfer using latent diffusion models.
99 shares
The second article introduces a new concept called cache-augmented generation (CAG) that uses the extended context windows of large language models (LLMs) to avoid real-time retrieval.
91 shares
The third article highlights the major issue of catastrophic forgetting when adjusting large language models (LLMs) to new tasks or domains.
39 shares
Repositories the letter featured.
10 items
The article QTPyLib Pythonic Algorithmic Trading discusses the use of Python in developing algorithmic trading strategies.
2,169 shares
A Machine Learning framework from scratch in Pure Mojo 🔥 is about building a machine learning framework using Pure Mojo.
428 shares
Collection of scripts to help with Options and Backtesting offers a set of scripts for options trading and backtesting.
2 shares
The piece A low code Machine Learning personalized ranking service for articles listings search results recommendations that boosts user engagement discusses a machine learning service that personalizes article rankings to enhance user engagement.
2,101 shares
This repository is used to extract the constituents of ETFs into a pandas DataFrame which could be used for further data exploration details how to extract ETF data for further analysis using a repository.
16 shares
The article gives a tutorial on using Python for constrained and unconstrained risk budgeting risk parity allocation.
123 shares
The article explores the use of AI in monitoring trending topics on social media.
1,900 shares
The article presents an open-source Python3 tool that converts visual content in images into Markdown format, supporting 80 languages.
2,087 shares
The article provides a guide on using a connector to access Binance's Public API.
2,100 shares
The article examines the patterns that enhance the scalability, reliability, and performance of large-scale systems.
59,757 shares
Industry news: funds, hiring, markets and regulation.
20 items
Investment management firm Ossiam has introduced a new fund providing market-neutral exposure to fixed income investments.
5 shares
Insight Investment has named Raman Srivastava as its new CEO, according to Pension & Investments.
5 shares
The article discusses the pros and cons of leaving a hedge fund tech job for a position in private equity.
4 shares
Paragon Capital Management, based in Singapore, has opened its first international office in Hong Kong to appeal to wealthy clients.
4 shares
Point72 Asset Management is venturing into the private credit market under the leadership of ex-Blackstone senior managing director, Todd Hirsch.
4 shares
Bloomberg reports that hedge funds predict the euro could equal or fall below the dollar due to its weak start to the year.
4 shares
FalconX, a cryptocurrency brokerage, is reportedly nearing the acquisition of crypto derivatives startup Arbelos Markets, says Bloomberg.
4 shares
Alfonso Peccatiello, ex-ING Germany investment head, is set to launch his new hedge fund, Palinuro Capital, on 13 January, according to Financial News London.
4 shares
Global hedge funds specializing in long/short stock trading saw their highest average returns since 2020, as per a Goldman Sachs note cited by Reuters.
3 shares
Rokos Capital Management's highest-paid member saw a 312% pay increase, earning £110.2m in the year ending 31 March 2024, reports Financial News.
3 shares
The article explores the advantages of working as a quantitative analyst in a specific region.
3 shares
Keystone Positive Change investment trust by Baillie Gifford is encouraging shareholders to reject a takeover bid from Saba Capital Management.
3 shares
Balyasny Asset Management's founder, Dmitry Balyasny, has reorganized the company's equities division due to poor performance in 2023.
2 shares
In late 2024, bullish bets on oil by investors reached a four-month peak, driven by hedge fund activities and expectations of Donald Trump's presidential comeback.
2 shares
Pershing Square Capital Management, led by Bill Ackman, has shut down its PSVII funds, a co-investment scheme designed to hold Universal Music Group NV shares.
2 shares
Third Point, an investment firm owned by Daniel S Loeb, plans to buy AS Birch Grove, a credit fund manager worth $8bn.
2 shares
Hedge funds are investing more in digital assets due to falling inflation and interest rates.
2 shares
Hindenburg Research has shorted Carvana, alleging financial misconduct and an unsustainable business model.
1 shares
Episodes on markets, quant methods and economics.
10 items
Max Osbon talks about the potential of tech investments, particularly in semiconductor companies like Nvidia, and the need to understand assets and predict market changes.
13 shares
Mark Rzepczynski discusses the differences between systematic and discretionary trading, the concept of risk versus uncertainty, and the difficulties of trading models in a podcast.
10 shares
Charles Rotblutt emphasizes the effect of market sentiment on investment choices and the necessity of a long-term investment approach.
10 shares
Meb Faber discusses the shift from traditional mutual funds to innovative ETFs, the importance of tax-efficient investing, and the growing trend of global endowment-style investing.
9 shares
The episode covers current market volatility, the effects of earnings season volatility, projected options volume for 2025, and the importance of bid calls in the Russell 2000.
8 shares
Meb Faber's audiobook Shareholder Yield A Better Approach to Dividend Investing, offering a comprehensive market strategy, is now free for podcast listeners.
4 shares
In the Investors First Podcast, Tom Lee of Fundstrat Global Advisors shares his predictions for the S&P 500, Bitcoin, and AI.
3 shares
Aleks Svetski, a Bitcoin enthusiast, discusses Bitcoin's potential to revolutionize global economies and societies with Michael Gayed on The Lead Lag Report.
2 shares
Housing analyst Amy Nixon talks about the paradox of limited supply and reduced demand in the post-pandemic housing market, and the impact of immigration policies.
2 shares
Ex-college athlete and real estate tycoon Kyle Kazan discusses his transition into the cannabis industry, its challenges, and growth opportunities through strategic partnerships and political changes.
0 shares
Posts from quant researchers on X.
13 items
The article reviews the use of machine learning in portfolio optimization, trading strategies, and sentiment analysis.
10 shares
The article explores a possible arbitrage opportunity in Canadian government bonds due to different day count conventions.
3 shares
The article announces a new research paper studying the success of trend-following strategies in the stock market.
3 shares
Article: The piece suggests six top books for understanding trading, investing, and managing portfolios.
2 shares
Article: The piece introduces a fresh compilation of recent studies on trading and investment.
1 shares
Article: The piece explores the idea of pairs trading within the cryptocurrency market.
1 shares
The author extends New Year greetings to followers of the Gregorian calendar in their first 2025 blog post.
0 shares
The article explores the potential impact of AI on user interfaces and compliance regulations in FinTech and DaaS, suggesting new revenue opportunities.
0 shares
The article examines how AI could alter SaaS revenue models, shifting from monthly rates to outcome-based pricing.
0 shares
NVIDIA has unveiled DIGITS, a compact Super Computer powered by GPU for AI, capable of running models with up to 600B parameters.
0 shares
The author suggests that the linked content is complex and requires careful examination to fully understand.
0 shares
Han and his team believe that investors often undervalue firm-specific profitability components, which, if properly sorted, can lead to substantial returns.
0 shares
The author investigates the impact of low-volatility in stocks, experimenting with different signals and combination strategies to enhance performance.
0 shares
Threads from r/quant, r/algotrading and friends.
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